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  <div class="section" id="mindspore-dataset-text-transforms-jiebatokenizer">
<h1>mindspore.dataset.text.transforms.JiebaTokenizer<a class="headerlink" href="#mindspore-dataset-text-transforms-jiebatokenizer" title="Permalink to this headline">¶</a></h1>
<dl class="class">
<dt id="mindspore.dataset.text.transforms.JiebaTokenizer">
<em class="property">class </em><code class="sig-prename descclassname">mindspore.dataset.text.transforms.</code><code class="sig-name descname">JiebaTokenizer</code><span class="sig-paren">(</span><em class="sig-param">hmm_path</em>, <em class="sig-param">mp_path</em>, <em class="sig-param">mode=JiebaMode.MIX</em>, <em class="sig-param">with_offsets=False</em><span class="sig-paren">)</span><a class="headerlink" href="#mindspore.dataset.text.transforms.JiebaTokenizer" title="Permalink to this definition">¶</a></dt>
<dd><p>使用Jieba分词器对中文字符串进行分词。</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>必须保证 HMMSEgment 算法和 MPSegment 算法所使用的字典文件的完整性。</p>
</div>
<p><strong>参数：</strong></p>
<ul class="simple">
<li><p><strong>hmm_path</strong> (str) -  HMMSegment 算法使用的字典文件路径，字典可在cppjieba官网获取，
详见 <a class="reference external" href="https://github.com/yanyiwu/cppjieba/tree/master/dict">cppjieba_github</a> 。</p></li>
<li><p><strong>mp_path</strong> (str) - MPSegment 算法使用的字典文件路径，字典可在cppjieba官网获取，
详见 <a class="reference external" href="https://github.com/yanyiwu/cppjieba/tree/master/dict">cppjieba_github</a> 。</p></li>
<li><p><strong>mode</strong> (JiebaMode, 可选) - Jieba分词使用的模式，可以取值为 JiebaMode.MP、JiebaMode.HMM 或 JiebaMode.MIX。默认值：JiebaMode.MIX。</p>
<ul>
<li><p><strong>JiebaMode.MP</strong>：使用最大概率法算法进行分词。</p></li>
<li><p><strong>JiebaMode.HMM</strong>：使用隐马尔可夫模型算法进行分词。</p></li>
<li><p><strong>JiebaMode.MIX</strong>：使用 MPSegment 和 HMMSegment 算法混合进行分词。</p></li>
</ul>
</li>
<li><p><strong>with_offsets</strong> (bool, 可选) - 是否输出标记(token)的偏移量，默认值：False。</p></li>
</ul>
<p><strong>异常：</strong></p>
<ul class="simple">
<li><p><strong>ValueError</strong> - 没有提供参数 <cite>hmm_path</cite> 或为None。</p></li>
<li><p><strong>ValueError</strong> - 没有提供参数 <cite>mp_path</cite> 或为None。</p></li>
<li><p><strong>TypeError</strong> - 参数 <cite>hmm_path</cite> 和 <cite>mp_path</cite> 类型不为string。</p></li>
<li><p><strong>TypeError</strong> - 参数 <cite>with_offsets</cite> 类型不为bool。</p></li>
</ul>
<p><strong>样例：</strong></p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">mindspore.dataset.text</span> <span class="kn">import</span> <span class="n">JiebaMode</span>
<span class="gp">&gt;&gt;&gt; </span><span class="c1"># If with_offsets=False, default output one column {[&quot;text&quot;, dtype=str]}</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">jieba_hmm_file</span> <span class="o">=</span> <span class="s2">&quot;/path/to/jieba/hmm/file&quot;</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">jieba_mp_file</span> <span class="o">=</span> <span class="s2">&quot;/path/to/jieba/mp/file&quot;</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">tokenizer_op</span> <span class="o">=</span> <span class="n">text</span><span class="o">.</span><span class="n">JiebaTokenizer</span><span class="p">(</span><span class="n">jieba_hmm_file</span><span class="p">,</span> <span class="n">jieba_mp_file</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="n">JiebaMode</span><span class="o">.</span><span class="n">MP</span><span class="p">,</span> <span class="n">with_offsets</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">text_file_dataset</span> <span class="o">=</span> <span class="n">text_file_dataset</span><span class="o">.</span><span class="n">map</span><span class="p">(</span><span class="n">operations</span><span class="o">=</span><span class="n">tokenizer_op</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="c1"># If with_offsets=False, then output three columns {[&quot;token&quot;, dtype=str], [&quot;offsets_start&quot;, dtype=uint32],</span>
<span class="gp">&gt;&gt;&gt; </span><span class="c1">#                                                   [&quot;offsets_limit&quot;, dtype=uint32]}</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">tokenizer_op</span> <span class="o">=</span> <span class="n">text</span><span class="o">.</span><span class="n">JiebaTokenizer</span><span class="p">(</span><span class="n">jieba_hmm_file</span><span class="p">,</span> <span class="n">jieba_mp_file</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="n">JiebaMode</span><span class="o">.</span><span class="n">MP</span><span class="p">,</span> <span class="n">with_offsets</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">text_file_dataset_1</span> <span class="o">=</span> <span class="n">text_file_dataset_1</span><span class="o">.</span><span class="n">map</span><span class="p">(</span><span class="n">operations</span><span class="o">=</span><span class="n">tokenizer_op</span><span class="p">,</span> <span class="n">input_columns</span><span class="o">=</span><span class="p">[</span><span class="s2">&quot;text&quot;</span><span class="p">],</span>
<span class="gp">... </span>                                              <span class="n">output_columns</span><span class="o">=</span><span class="p">[</span><span class="s2">&quot;token&quot;</span><span class="p">,</span> <span class="s2">&quot;offsets_start&quot;</span><span class="p">,</span> <span class="s2">&quot;offsets_limit&quot;</span><span class="p">],</span>
<span class="gp">... </span>                                              <span class="n">column_order</span><span class="o">=</span><span class="p">[</span><span class="s2">&quot;token&quot;</span><span class="p">,</span> <span class="s2">&quot;offsets_start&quot;</span><span class="p">,</span> <span class="s2">&quot;offsets_limit&quot;</span><span class="p">])</span>
</pre></div>
</div>
<dl class="method">
<dt id="mindspore.dataset.text.transforms.JiebaTokenizer.add_word">
<code class="sig-name descname">add_word</code><span class="sig-paren">(</span><em class="sig-param">word</em>, <em class="sig-param">freq=None</em><span class="sig-paren">)</span><a class="headerlink" href="#mindspore.dataset.text.transforms.JiebaTokenizer.add_word" title="Permalink to this definition">¶</a></dt>
<dd><p>将用户定义的词添加到 JiebaTokenizer 的字典中。</p>
<p><strong>参数：</strong></p>
<ul class="simple">
<li><p><strong>word</strong> (str) - 要添加到 JiebaTokenizer 词典中的单词，注意通过此接口添加的单词不会被写入本地的模型文件中。</p></li>
<li><p><strong>freq</strong> (int，可选) - 要添加的单词的频率。频率越高，单词被分词的机会越大。默认值：None，使用默认频率。</p></li>
</ul>
<p><strong>样例：</strong></p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">mindspore.dataset.text</span> <span class="kn">import</span> <span class="n">JiebaMode</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">jieba_hmm_file</span> <span class="o">=</span> <span class="s2">&quot;/path/to/jieba/hmm/file&quot;</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">jieba_mp_file</span> <span class="o">=</span> <span class="s2">&quot;/path/to/jieba/mp/file&quot;</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">jieba_op</span> <span class="o">=</span> <span class="n">text</span><span class="o">.</span><span class="n">JiebaTokenizer</span><span class="p">(</span><span class="n">jieba_hmm_file</span><span class="p">,</span> <span class="n">jieba_mp_file</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="n">JiebaMode</span><span class="o">.</span><span class="n">MP</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">sentence_piece_vocab_file</span> <span class="o">=</span> <span class="s2">&quot;/path/to/sentence/piece/vocab/file&quot;</span>
<span class="gp">&gt;&gt;&gt; </span><span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="n">sentence_piece_vocab_file</span><span class="p">,</span> <span class="s1">&#39;r&#39;</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
<span class="gp">... </span>    <span class="k">for</span> <span class="n">line</span> <span class="ow">in</span> <span class="n">f</span><span class="p">:</span>
<span class="gp">... </span>        <span class="n">word</span> <span class="o">=</span> <span class="n">line</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39;,&#39;</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span>
<span class="gp">... </span>        <span class="n">jieba_op</span><span class="o">.</span><span class="n">add_word</span><span class="p">(</span><span class="n">word</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">text_file_dataset</span> <span class="o">=</span> <span class="n">text_file_dataset</span><span class="o">.</span><span class="n">map</span><span class="p">(</span><span class="n">operations</span><span class="o">=</span><span class="n">jieba_op</span><span class="p">,</span> <span class="n">input_columns</span><span class="o">=</span><span class="p">[</span><span class="s2">&quot;text&quot;</span><span class="p">])</span>
</pre></div>
</div>
</dd></dl>

<dl class="method">
<dt id="mindspore.dataset.text.transforms.JiebaTokenizer.add_dict">
<code class="sig-name descname">add_dict</code><span class="sig-paren">(</span><em class="sig-param">user_dict</em><span class="sig-paren">)</span><a class="headerlink" href="#mindspore.dataset.text.transforms.JiebaTokenizer.add_dict" title="Permalink to this definition">¶</a></dt>
<dd><p>将用户定义的词添加到 JiebaTokenizer 的字典中。</p>
<p><strong>参数：</strong></p>
<ul>
<li><p><strong>user_dict</strong> (Union[str, dict]) - 有两种输入方式。可以通过指定jieba字典格式的文件路径加载。
要求的jieba字典格式为：[word，freq]，如：</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">word1</span> <span class="n">freq1</span>
<span class="n">word2</span> <span class="kc">None</span>
<span class="n">word3</span> <span class="n">freq3</span>
</pre></div>
</div>
<p>也可以通过Python dict加载，要求的 Python 字典格式为：{word1:freq1, word2:freq2,…}。
只有用户提供的文件中有效的词对才会被添加到字典中，无的效输入行将被忽略，且不返回错误或警告状态。</p>
</li>
</ul>
<p><strong>样例：</strong></p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">mindspore.dataset.text</span> <span class="kn">import</span> <span class="n">JiebaMode</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">jieba_hmm_file</span> <span class="o">=</span> <span class="s2">&quot;/path/to/jieba/hmm/file&quot;</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">jieba_mp_file</span> <span class="o">=</span> <span class="s2">&quot;/path/to/jieba/mp/file&quot;</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">user_dict</span> <span class="o">=</span> <span class="p">{</span><span class="s2">&quot;男默女泪&quot;</span><span class="p">:</span> <span class="mi">10</span><span class="p">}</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">jieba_op</span> <span class="o">=</span> <span class="n">text</span><span class="o">.</span><span class="n">JiebaTokenizer</span><span class="p">(</span><span class="n">jieba_hmm_file</span><span class="p">,</span> <span class="n">jieba_mp_file</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="n">JiebaMode</span><span class="o">.</span><span class="n">MP</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">jieba_op</span><span class="o">.</span><span class="n">add_dict</span><span class="p">(</span><span class="n">user_dict</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">text_file_dataset</span> <span class="o">=</span> <span class="n">text_file_dataset</span><span class="o">.</span><span class="n">map</span><span class="p">(</span><span class="n">operations</span><span class="o">=</span><span class="n">jieba_op</span><span class="p">,</span> <span class="n">input_columns</span><span class="o">=</span><span class="p">[</span><span class="s2">&quot;text&quot;</span><span class="p">])</span>
</pre></div>
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